Increasing advances in computer technology (e.g., microprocessor speed, memory capacity, data transfer bandwidth, software functionality . . . ) have generally contributed to increased computer application in various industries. Today, computer users produce and manage large amounts of data or information, as compared to their respective work load in prior years. Generally, computer users now often multitask numerous items (e.g., documents, spreadsheets, statements, presentations, media . . . ) simultaneously and in conjunction with applications that facilitate management of these items.
Typically, a continuing problem in computer systems has been handling the growing amount of information or data available. The sheer amount of information being stored on disks or other media for databases in some form has been increasing dramatically. While files and disks were measured in thousands of bytes a few decades ago—at that time being millions of bytes (megabytes), followed by billions of bytes (gigabytes)—now databases of a million megabytes (terabytes) and even billions of megabytes are being created and employed in day-to-day activities.
As such, various software-based tools have been developed to aid user(s) with multi-tasking. One very powerful tool is a file data retrieval and organization system, which allows users to quickly view and access directories and their respective content. For example, a file management system can present directories and/or contents via a tree-based hierarchy (e.g., object hierarchy)—which can be a logical and user intuitive scheme for presentation of information associated with file management.
At the same time, in designing such tools a key idea of the database-based operating system should generally be an ability to find desired items quickly by executing a query that can involve a limited number of item properties. While such query approach can seem powerful, the success of the system generally depends on an ability to create a user interface that will make queries simple and intuitive for average users. For example, in its native form, database queries, (e.g. expressed in T-SQL language), can be difficult to handle even for professional programmers, much less the average end user. In addition, it is desirable for the query to speculate a relevance of a result for a given context.
At the same time, a typical rule of thumb based on the Pareto principle seems to apply to data base management, leading to much waste and inefficiency. Such rule of thumb, also referred to as the 80/20 rule, as applied to database list management seems to suggest that it is likely that only 20% of the data is accessed 80% of the time by a particular user. The remaining 80% of the data is accessed much less frequently, if at all. As the size of a database continues to grow, keeping the rarely accessed portion of the data base online in disk storage connected to a computer system can be an increasingly costly and wasteful strategy.
In general, many users employing a data base list such as a list of people now face a deluge of information from which to sort through and/or respond to (e.g. e-mails), such that the capability of being able to send, receive and process information through the data base list has almost become a hindrance to being productive. Accordingly, with such large numbers of people on a given list, it hence becomes difficult to manage information according to which person on the list is important, and who is not as important, without substantially expending valuable time for such determination. At the same time from a social standpoint, ordering a list of people, based merely on an importance criteria, can create negative connotations feelings of inferiority for the person who is categorized below others.
Therefore, there is a need to overcome the aforementioned deficiencies associated with conventional systems and methodologies related to data base lists.